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ORCIDArunselvan Ramaswamy
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2020 – today
- 2024
[j13]Ayeh Mahjoubi
, Arunselvan Ramaswamy, Karl-Johan Grinnemo:
An Online Simulated Annealing-Based Task Offloading Strategy for a Mobile Edge Architecture. IEEE Access 12: 70707-70718 (2024)- [c11]Arunselvan Ramaswamy, Yunpeng Ma, Stefan Alfredsson, Fran Collyer, Anna Brunström:
Information Theoretic Deductions Using Machine Learning with an Application in Sociology. ICPRAM 2024: 320-328 - [c10]Hifza Khalid, Arunselvan Ramaswamy, Simone Ferlin, Alva L. Couch:
Modeling Batch Tasks Using Recurrent Neural Networks in Co-Located Alibaba Workloads. ICPRAM 2024: 558-569 - 2023
- [j12]Haitham Afifi, Arunselvan Ramaswamy, Holger Karl:
Reinforcement learning for autonomous vehicle movements in wireless multimedia applications. Pervasive Mob. Comput. 92: 101799 (2023) - [c9]Arunselvan Ramaswamy:
Gradient Clipping in Deep Learning: A Dynamical Systems Perspective. ICPRAM 2023: 107-114 - [i19]Adrian Redder, Arunselvan Ramaswamy, Holger Karl:
Stability and Convergence of Distributed Stochastic Approximations with large Unbounded Stochastic Information Delays. CoRR abs/2305.07091 (2023) - [i18]Arunselvan Ramaswamy, Shalabh Bhatnagar, Naman Saxena:
A Framework for Provably Stable and Consistent Training of Deep Feedforward Networks. CoRR abs/2305.12125 (2023) - 2022
- [j11]Arunselvan Ramaswamy, Shalabh Bhatnagar:
Analyzing Approximate Value Iteration Algorithms. Math. Oper. Res. 47(3): 2138-2159 (2022) - [j10]Arunselvan Ramaswamy, Adrian Redder, Daniel E. Quevedo:
Optimization Over Time-Varying Networks and Unbounded Information Delays. IEEE Trans. Autom. Control. 67(8): 4131-4137 (2022) - [j9]Arunselvan Ramaswamy, Eyke Hüllermeier:
Deep Q-Learning: Theoretical Insights From an Asymptotic Analysis. IEEE Trans. Artif. Intell. 3(2): 139-151 (2022) - [c8]Adrian Redder, Arunselvan Ramaswamy, Holger Karl:
Age of Information Process under Strongly Mixing Communication - Moment Bound, Mixing Rate and Strong Law. Allerton 2022: 1-8 - [c7]Pritha Gupta, Arunselvan Ramaswamy, Jan Peter Drees, Eyke Hüllermeier, Claudia Priesterjahn, Tibor Jager:
Automated Information Leakage Detection: A New Method Combining Machine Learning and Hypothesis Testing with an Application to Side-channel Detection in Cryptographic Protocols. ICAART (2) 2022: 152-163 - [c6]Adrian Redder, Arunselvan Ramaswamy, Holger Karl:
Multi-agent Policy Gradient Algorithms for Cyber-physical Systems with Lossy Communication. ICAART (1) 2022: 282-289 - [i17]Adrian Redder, Arunselvan Ramaswamy, Holger Karl:
Asymptotic Convergence of Deep Multi-Agent Actor-Critic Algorithms. CoRR abs/2201.00570 (2022) - [i16]Adrian Redder, Arunselvan Ramaswamy, Holger Karl:
Distributed gradient-based optimization in the presence of dependent aperiodic communication. CoRR abs/2201.11343 (2022) - 2021
- [j8]Arunselvan Ramaswamy, Shalabh Bhatnagar, Daniel E. Quevedo:
Asynchronous Stochastic Approximations With Asymptotically Biased Errors and Deep Multiagent Learning. IEEE Trans. Autom. Control. 66(9): 3969-3983 (2021) - [c5]Haitham Afifi, Arunselvan Ramaswamy, Holger Karl:
A Reinforcement Learning QoI/QoS-Aware Approach in Acoustic Sensor Networks. CCNC 2021: 1-6 - [c4]Jan Peter Drees, Pritha Gupta, Eyke Hüllermeier, Tibor Jager, Alexander Konze, Claudia Priesterjahn, Arunselvan Ramaswamy, Juraj Somorovsky:
Automated Detection of Side Channels in Cryptographic Protocols: DROWN the ROBOTs! AISec@CCS 2021: 169-180 - [c3]Haitham Afifi, Arunselvan Ramaswamy, Holger Karl:
Reinforcement Learning for Autonomous Vehicle Movements in Wireless Sensor Networks. ICC 2021: 1-6 - [i15]Adrian Redder, Arunselvan Ramaswamy, Holger Karl:
Practical sufficient conditions for convergence of distributed optimisation algorithms over communication networks with interference. CoRR abs/2105.04230 (2021) - [i14]Jan Peter Drees, Pritha Gupta, Eyke Hüllermeier, Tibor Jager, Alexander Konze, Claudia Priesterjahn, Arunselvan Ramaswamy, Juraj Somorovsky:
Automated Detection of Side Channels in Cryptographic Protocols: DROWN the ROBOTs! IACR Cryptol. ePrint Arch. 2021: 591 (2021) - 2020
- [j7]Alex S. Leong, Arunselvan Ramaswamy, Daniel E. Quevedo, Holger Karl, Ling Shi:
Deep reinforcement learning for wireless sensor scheduling in cyber-physical systems. Autom. 113: 108759 (2020) - [c2]Arunselvan Ramaswamy:
DSPG: Decentralized Simultaneous Perturbations Gradient Descent Scheme. PDP 2020: 54-62 - [i13]Arunselvan Ramaswamy:
Theory of Deep Q-Learning: A Dynamical Systems Perspective. CoRR abs/2008.10870 (2020)
2010 – 2019
- 2019
- [j6]Arunselvan Ramaswamy, Shalabh Bhatnagar:
Stability of Stochastic Approximations With "Controlled Markov" Noise and Temporal Difference Learning. IEEE Trans. Autom. Control. 64(6): 2614-2620 (2019) - [c1]Jonas König, Simon Malberg, Martin Martens, Sebastian Niehaus, Artus Krohn-Grimberghe, Arunselvan Ramaswamy:
Multi-stage Reinforcement Learning for Object Detection. CVC (1) 2019: 178-191 - [i12]Arunselvan Ramaswamy:
DSPG: Decentralized Simultaneous Perturbations Gradient Descent Scheme. CoRR abs/1903.07050 (2019) - [i11]Adrian Redder, Arunselvan Ramaswamy, Daniel E. Quevedo:
Deep reinforcement learning for scheduling in large-scale networked control systems. CoRR abs/1905.05992 (2019) - 2018
- [j5]Burak Demirel, Arunselvan Ramaswamy, Daniel E. Quevedo, Holger Karl:
DeepCAS: A Deep Reinforcement Learning Algorithm for Control-Aware Scheduling. IEEE Control. Syst. Lett. 2(4): 737-742 (2018) - [j4]Arunselvan Ramaswamy, Shalabh Bhatnagar:
Analysis of Gradient Descent Methods With Nondiminishing Bounded Errors. IEEE Trans. Autom. Control. 63(5): 1465-1471 (2018) - [i10]Burak Demirel, Arunselvan Ramaswamy, Daniel E. Quevedo, Holger Karl:
DeepCAS: A Deep Reinforcement Learning Algorithm for Control-Aware Scheduling. CoRR abs/1803.02998 (2018) - [i9]Alex S. Leong, Arunselvan Ramaswamy, Daniel E. Quevedo, Holger Karl, Ling Shi:
Deep Reinforcement Learning for Wireless Sensor Scheduling in Cyber-Physical Systems. CoRR abs/1809.05149 (2018) - [i8]Jonas König, Simon Malberg, Martin Martens, Sebastian Niehaus, Artus Krohn-Grimberghe, Arunselvan Ramaswamy:
Multi-Stage Reinforcement Learning For Object Detection. CoRR abs/1810.10325 (2018) - 2017
- [j3]Arunselvan Ramaswamy, Shalabh Bhatnagar:
A Generalization of the Borkar-Meyn Theorem for Stochastic Recursive Inclusions. Math. Oper. Res. 42(3): 648-661 (2017) - [i7]Arunselvan Ramaswamy, Shalabh Bhatnagar:
Conditions for Stability and Convergence of Set-Valued Stochastic Approximations: Applications to Approximate Value and Fixed point Iterations with Noise. CoRR abs/1709.04673 (2017) - 2016
- [i6]Arunselvan Ramaswamy, Shalabh Bhatnagar:
Gradient-based learning algorithms with constant-error estimators: stability and convergence. CoRR abs/1604.00151 (2016) - 2015
- [i5]Arunselvan Ramaswamy, Shalabh Bhatnagar:
A Generalization of the Borkar-Meyn Theorem for Stochastic Recursive Inclusions. CoRR abs/1502.01953 (2015) - [i4]Arunselvan Ramaswamy, Shalabh Bhatnagar:
Stochastic recursive inclusions with two timescales. CoRR abs/1502.01956 (2015) - [i3]Arunselvan Ramaswamy, Shalabh Bhatnagar:
Stability of Stochastic Approximations with 'Controlled Markov' Noise and Temporal Difference Learning. CoRR abs/1504.06043 (2015) - 2014
- [j2]Manu Basavaraju, L. Sunil Chandran, Deepak Rajendraprasad, Arunselvan Ramaswamy:
Rainbow Connection Number and Radius. Graphs Comb. 30(2): 275-285 (2014) - [j1]Manu Basavaraju, L. Sunil Chandran, Deepak Rajendraprasad, Arunselvan Ramaswamy:
Rainbow Connection Number of Graph Power and Graph Products. Graphs Comb. 30(6): 1363-1382 (2014) - 2011
- [i2]Manu Basavaraju, L. Sunil Chandran, Deepak Rajendraprasad, Arunselvan Ramaswamy:
Rainbow Connection Number of Graph Power and Graph Products. CoRR abs/1104.4190 (2011) - 2010
- [i1]Manu Basavaraju, L. Sunil Chandran, Deepak Rajendraprasad, Arunselvan Ramaswamy:
Rainbow Connection Number and Radius. CoRR abs/1011.0620 (2010)
Coauthor Index
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